Version history

{
  "scope": "Awake mouse visual cortex, 2P calcium imaging",
  "claim_text": "A new dynamic Zebra-noise stimulus combined with a wavelet-based analysis model enables rapid characterization of position, orientation, size, spatial frequency, drift rate and direction tuning for thousands of mouse-V1 neurons in just five minutes of stimulus (repeated three times) using two-photon calcium imaging — significantly extending the throughput envelope of feature-tuning measurements in mouse cortex.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1167/jov.26.1.1",
    "claim": "A new dynamic Zebra-noise stimulus combined with a wavelet-based analysis model enables rapid characterization of position, orientation, size, spatial frequency, drift rate and direction tuning for thousands of mouse-V1 neurons in just five minutes of stimulus (repeated three times) using two-photon calcium imaging — significantly extending the throughput envelope of feature-tuning measurements in mouse cortex.",
    "cite_key": "Skriabine2026",
    "evidence": "Stimulus + wavelet model comparison vs traditional stimuli; thousand-neuron-scale tuning measurements in mouse V1.",
    "effect_size": "thousands of neurons tuned across 6 stimulus dimensions in 5 min × 3 repeats",
    "text_access": "fulltext",
    "study_system": "Awake mouse visual cortex, 2P calcium imaging",
    "argument_role": "supporting",
    "replication_status": "single-study-methods",
    "claim_source_sentence": "The method proved efficient, requiring only 5 minutes of stimulus (repeated three times) to characterize the tuning of thousands of neurons across visual areas.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": "The method proved efficient, requiring only 5 minutes of stimulus (repeated three times) to characterize the tuning of thousands of neurons across visual areas."
  },
  "section_id": "section_16",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_16_evidence_package.json",
  "effect_size": "thousands of neurons tuned across 6 stimulus dimensions in 5 min × 3 repeats",
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-16-synthesis",
  "source_kind": "review_finding",
  "source_path": "evidence/section_16_evidence_package.json",
  "source_refs": [
    "paper:paper-e3ab0a91f3c5"
  ],
  "source_span": "The method proved efficient, requiring only 5 minutes of stimulus (repeated three times) to characterize the tuning of thousands of neurons across visual areas.",
  "study_system": "Awake mouse visual cortex, 2P calcium imaging",
  "evidence_refs": [
    {
      "ref": "paper:paper-e3ab0a91f3c5"
    }
  ],
  "section_title": "16. Synthesis — which computational claims the mouse-cortex E→E empirical record actually supports, where the bottleneck observations are, and what an inhibition-free, single-species, basic-research analytic framing misses",
  "source_policy": {
    "mode": "public_source_pointer_with_short_context",
    "notes": [
      "Local review repositories are read-only inputs.",
      "SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose."
    ],
    "source_commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
    "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
  },
  "evidence_summary": "Stimulus + wavelet model comparison vs traditional stimuli; thousand-neuron-scale tuning measurements in mouse V1.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "single-study-methods",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-16-synthesis",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_16_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}